David Kaftan is a senior system analyst and award-winning data scientist with 11 years of experience building production-ready analytic systems and forecasting models. He combines strong software engineering practices (automated testing, CI, packaged R libraries) with applied modeling and ML, having deployed large-scale energy and public-health forecasts to Azure and SQL-backed production pipelines. His work informed public health responses (Mpox forecasting for NYC) and program planning for foundations like Bill & Melinda Gates and CHAI, and he presented findings at CROI and ODSC Europe. He has led cross-disciplinary projects from PyTorch computer vision on satellite imagery to TensorFlow-based feature reduction for million-customer energy forecasts. David also teaches advanced computer engineering and has published first-author research on data generation, reflecting a rare mix of academic rigor and operational delivery. Based in Milwaukee, he’s skilled at turning complex epidemiological and utility datasets into reliable, auditable decision tools.
11 years of coding experience
8 years of employment as a software developer
Master's degree, Electrical and Computer Engineering, Master's degree, Electrical and Computer Engineering at Marquette University
High School Diploma, High School Diploma at Creighton Prep
A translation of the popular R library quantreg to python for quantile regression
Contributions:4 reviews, 36 commits, 23 PRs in 1 year 2 months
pythonquantile-regressionrr-library
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